Canisius Golden Griffins
2026 Team Stats (27 games)
54.8
PPG
67.1
Opp
-12.3
Margin
39.3%
FG%
28.2%
3P%
72.4%
FT%
35.9
RPG
11.2
APG
23.5
TO
80.0
Pace
Model Outputs
2025-2026
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 871 (#555) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -4.5 (#356) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.304 (#557) | AdjO 56.0 | AdjD 65.1 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.267 (#414) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Recency Ensemble Recency Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and recency points off/def. More → | 0.259 (#435) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 706 (#577) | RD 175 | GP 27 |
2026 Schedule & Results
2026 Roster
Minutes by Position
The surface stays filled across the five on-court roles. Use the labels or legend to isolate how each player absorbs guard-to-big minutes.
| Player | Pos | GP | MIN | PTS | REB | AST | STL | BLK | TO | FGA | Numbers | PM | PM/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
S. Gailes
|
F | 24 | 29.1 | 12.2 | 8.5 | 0.7 | 0.6 | 0.0 | 3.0 | 8.6 | 10.4 | -66 | -3.5 | -4.5 | 48.3 | 33.3 | 77.3 | -3.01 | 56.7 | 48.8 |
F. Wittenberg
|
G | 27 | 28.3 | 9.3 | 5.5 | 2.5 | 1.0 | 0.4 | 3.9 | 7.9 | 7.0 | -13 | -0.6 | -0.8 | 39.6 | 23.3 | 76.8 | 0.6 | 49.1 | 41.3 |
Y. Djibril
|
F | 27 | 27.5 | 9.1 | 4.6 | 1.9 | 0.9 | 0.4 | 2.9 | 7.1 | 7.0 | 38 | 1.7 | 2.4 | 47.6 | 21.1 | 65.6 | 1.11 | 53.1 | 48.7 |
I. Rey Pineda
|
F | 27 | 21.6 | 5.5 | 2.0 | 1.0 | 1.0 | 0.1 | 2.5 | 5.7 | 1.5 | 32 | 1.5 | 2.4 | 38.3 | 31.8 | 64.3 | 3.33 | 46.2 | 45.1 |
C. Clay
|
G | 27 | 24.4 | 4.5 | 1.5 | 1.0 | 0.3 | 0.0 | 1.4 | 4.0 | 1.9 | -9 | -0.4 | -0.7 | 39.4 | 38.1 | 70.6 | -1.21 | 52.4 | 50.5 |
M. Copple
|
G | 27 | 17.3 | 3.7 | 1.8 | 1.1 | 0.4 | 0.1 | 1.8 | 4.0 | 1.2 | 28 | 1.3 | 3.0 | 31.2 | 29.2 | 83.3 | 1.14 | 44.3 | 43.1 |
A. Auston
|
G | 27 | 14.6 | 3.3 | 2.2 | 1.3 | 0.4 | 0.0 | 2.5 | 3.6 | 1.2 | 32 | 1.5 | 3.9 | 30.2 | 25.0 | 66.7 | 2.54 | 40.8 | 35.9 |
I. Feliz
|
F | 27 | 10.7 | 3.1 | 2.4 | 0.3 | 0.0 | 0.1 | 1.3 | 3.1 | 1.6 | -43 | -2.0 | -7.5 | 39.3 | 0 | 66.7 | -2.78 | 43.8 | 39.3 |
K. Bess
|
G | 24 | 12.3 | 3.0 | 2.0 | 0.5 | 0.2 | 0.1 | 1.5 | 3.1 | 1.2 | 5 | 0.2 | 0.7 | 31.1 | 25.0 | 88.9 | 1.55 | 43.3 | 37.2 |
M. Mescall
|
G | 27 | 7.7 | 1.4 | 0.3 | 0.5 | 0.1 | 0.0 | 0.6 | 2.3 | -0.6 | -39 | -1.8 | -8.1 | 22.2 | 17.6 | 0 | -2.15 | 29.4 | 29.4 |
E. Van Der Woude
|
C | 17 | 9.4 | 1.2 | 1.5 | 0.3 | 0.2 | 0.5 | 1.2 | 1.1 | 1.4 | -8 | -0.5 | -1.9 | 47.4 | 0 | 37.5 | -0.04 | 46.6 | 47.4 |
A. Moses
|
G | 17 | 8.6 | 0.8 | 0.8 | 0.5 | 0.1 | 0.1 | 0.5 | 0.5 | 1.2 | 4 | 0.4 | 2.0 | 55.6 | 50.0 | 100.0 | 1.88 | 74.2 | 72.2 |
A. Parker
|
G | 4 | 5.8 | 0.5 | 0.8 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8 | 0.5 | -5 | -5.0 | -93.0 | 0.0 | 0.0 | 100.0 | -1.1 | 25.8 | 0.0 |
S. Randolph
|
G | 24 | 2.0 | 0.1 | 0.4 | 0.0 | 0.0 | 0.0 | 0.2 | 0.2 | 0.1 | -22 | -1.1 | -32.3 | 0.0 | 0 | 50.0 | -3.55 | 14.8 | 0.0 |
Jania Akins
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Numbers/Game vs RAPM
X-axis = Numbers/Game (PTS+REB+AST+STL+BLK-TO-FGA), Y-axis = RAPM.
Advanced: Numbers = PTS+REB+AST+STL+BLK-TO-FGA, PM = total +/-, PM/G = per game, PM/40 = per 40 minutes, RAPM = Regularized Adj Plus-Minus, TS% = True Shooting, eFG% = Effective FG